Gil Levi
Impact in
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- Face recognition and analysis
- Face and Expression Recognition
- Generative Adversarial Networks and Image Synthesis
- Video Surveillance and Tracking Methods
- Advanced Image and Video Retrieval Techniques
- Human Pose and Action Recognition
- Signal Processing top 5%
- Biometric Identification and Security
Papers in
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- Face and Expression Recognition 2
- Face recognition and analysis 2
- Human Pose and Action Recognition 2
- Image Retrieval and Classification Techniques 2
- Video Analysis and Summarization 2
- Image Processing and 3D Reconstruction 1
- Genetics 2
- Dermatoglyphics and Human Traits 2
- Co-authors
- Tal Hassner (4 shared papers)Lior Wolf (3 shared papers)Nachum Dershowitz (1 shared paper)Angélo Paci (2 shared papers)Matteo Ceccarelli (2 shared papers)A. Grasselli (2 shared papers)
- Journals
- PubMed (2 papers)arXiv (Cornell University) (1 paper)
- Partner nations
- Israel
In The Last Decade
Gil Levi
8 papers receiving 991 citations
Gil Levi's Hit Papers
Peers
Comparison fields: 5 of 102
- Computer Vision and Pattern Recognition 873
- Signal Processing 226
- Experimental and Cognitive Psychology 172
- Human-Computer Interaction 38
- Artificial Intelligence 171
Countries citing papers authored by Gil Levi
This map shows the geographic impact of Gil Levi's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Gil Levi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gil Levi more than expected).
Fields of papers citing papers by Gil Levi
This network shows the impact of papers produced by Gil Levi. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Gil Levi. The network helps show where Gil Levi may publish in the future.
Co-authors
The 6 scholars most cited alongside Gil Levi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Age and gender classification using convolutional neural networks Hit paper breakdown → | 2015 | 720 |
| 2 | 2015 | 222 | |
| 3 | 2016 | 90 | |
| 4 | 2017 | 22 | |
| 5 | Temporal Tessellation for Video Annotation and Summarization. | 2016 | 4 |
| 6 | 2018 | 3 | |
| 7 | [Attempted quantitative analysis of dermatoglyphics with the electronic computer]. | 1968 | 1 |
| 8 | An approach to quantitative analysis of dermatoglyphics by digital computer. | 1969 | 1 |
| 9 | 2018 | 0 |
About Gil Levi
Gil Levi is a scholar working on Computer Vision and Pattern Recognition, Genetics, Space and Planetary Science, Signal Processing and Artificial Intelligence, having authored 9 papers that have together received 1.1k indexed citations. Recurring topics across this work include Face and Expression Recognition (2 papers), Face recognition and analysis (2 papers), Dermatoglyphics and Human Traits (2 papers), Human Pose and Action Recognition (2 papers), Image Retrieval and Classification Techniques (2 papers), Video Analysis and Summarization (2 papers), Natural Language Processing Techniques (1 paper) and Image Processing and 3D Reconstruction (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (873 citations), Signal Processing (226 citations), Experimental and Cognitive Psychology (172 citations), Human-Computer Interaction (38 citations) and Artificial Intelligence (171 citations). Gil Levi has collaborated with scholars based in Israel. Frequent co-authors include Tal Hassner, Lior Wolf, Nachum Dershowitz, Angélo Paci, Matteo Ceccarelli and A. Grasselli. Their work appears in journals such as PubMed and arXiv (Cornell University).
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.